Bio Research Interests Plain Language Summary Publications Appointments

Pharmacogenomic epidemiology is a research area that utilizes epidemiologic methodologies to interrogate pharmacogenomic questions. This research focuses on the use of observational datasets or secondary analyses of clinical trials to evaluate the impact of genetic variation and tumour genomics within pharmacodynamic and pharmacokinetic pathways of therapies on important patient outcomes, such as treatment response, survival or toxicity.

The Liu laboratory, known as AMPPEL (Applied Molecular Profiling Pharmacogenomic Epidemiologic Laboratory) involves a wet component (cell line, primary human xenografts, and primary human tissues, functional assays) and a dry laboratory (clinic-epidemiologic recruitment, data collection, sample acquisition, statistical analysis, epidemiologic and health services outcomes research analyses). The application of molecular epidemiologic methods to pharmacogenetics has provided new opportunities to evaluate rigorously the role of genomic factors in cancer treatment outcomes and toxicity. When large clinical trials involving the drugs of interest are available, secondary analysis of such trials is the preferred method of studying pharmacogenetics. However, there are many instances, such as in rare tumours or when trying to evaluate pharmacogenomics of standard chemotherapy or radiotherapy treatments, where clinical trials are not available to answer important pharmacogenetic questions. Under these circumstances, the role of carefully planned prospective observational studies becomes instrumental to answer both pharmacogenomic and cancer prognosis questions. The quality of results obtainable from these studies is highly dependent on the methods used to recruit patients, to obtain and process samples, to accurately measure genetic markers, to determine accurate phenotypes and outcomes, and to perform appropriate statistical analysis. In addition, pharmacogenomic functional assays and testing are an important component. Therefore, PGE results from these high quality observational studies and clinical trials, the goal of much of AMPPEL's efforts, have strong potential to impact on patient risk stratification and in the choice of appropriate therapies. Dr. Liu is the overall lead PI of the CARMA BROS study (Canadian Rare Molecular Alteration Basket-umbrella Real-world Observational Study; NCT04151342), and site PI of PALEOS (Pan-Canadian Lung cancEr Observational Study; NCT04706754).

A major impediment to performing PGE research has been the lack of systematic collection of toxicity outcomes outside of the clinical trial setting. Dr. Liu is co-director of the ON-PROST ACRU (Ontario Patient Reported Outcomes of Symptoms and Toxicity Applied Clinical Research Unit) funded by Cancer Care Ontario (CCO). This clinical research unit is envisioned as a virtual laboratory for piloting different methods for systematically collecting patient symptoms and toxicity as part of routine care and for research purposes, developing province-wide consensus on what toxicities and symptoms to collect, to support the computer adaptive technology required for province-wide implementation. The majority of pilots are beginning at PMH (lung, head and neck, gastro-esophageal, testicular cancers), in areas that correspond to ongoing molecular epidemiological studies.

Evaluations of Clinical Utility and Clinical Uptake of pharmacogenomic testing are critical to translation from bench to bedside. In the era of personalized medicine, evaluating whether patients understand what pharmacogenomic testing means and involves, their attitude and preferences is important. Through interview-based research utilizing theoretical scenarios and either trade-off testing or conjoint testing, AMPPEL has been ascertaining PMH patient and physician attitudes, understanding and preferences for pharmacogenetic testing.

Dr. Liu is co-lead on 2BLAST (Biostatistics and bioinformatics for the longitudinal analysis of symptoms and toxicity) data science project at Princess Margaret Cancer Centre and co-lead on MBLAST (Machine Learning and Biostatistics for the longitudinal analysis of symptoms and toxicity). This research integrates use of the electronic health record with patient-reported data for analysis of patterns of care and outcomes, using machine learning and natural language processing methods. Some of these analyses are helping the 9^th Edition Lung Cancer Staging Project. He is co-leading these efforts with Dr. Wei Xu (Biostatistics) and Dr. Robert Grant (Machine Learning).

AMPPEL is performing PGE evaluations in clinical trials and observational studies, using archival tissue, fresh tissue, blood and other surrogate tissues. The methodologic approaches used include: candidate-based analyses, pharmacokinetic (PK) and pharmacodynamic (PD) pathway analyses, genome-wide association studies (GWAS) and post-GWAS analyses (includes methods development), and in the next few years, Next Generation Sequencing (Whole Exome, Whole Genome Sequencing). In addition, AMPPEL has recruited hundreds of patients into molecular epidemiologic studies, including patients with Lung, Head and Neck, Gastro-esophageal, hepatobiliary, pancreatic, and testicular cancer patients, thymomas and mesotheliomas. The laboratory has helped to integrate and coordinate consenting, recruitment, data collection, data management, quality control and clinico-epidemiologic analyses for multiple cancer site

Dr. Liu has been PI of a five-year CCSRI Impact Grant, lung cancer primary derived xenograft program, and is currently PI of a subsequent CIHR-funded grant on primary derived organoids of lung cancer, OPTIMAL (Organoids to guide Post-resistance Therapy In driver MutAted Lung cancers (OPTIMAL). He is also co-lead of POLOR (Patient-derived Organoids of Lung cancer to understand Osimertinib Resistance), an industry sponsored organoid project. He co-leads these research programs with Dr. Ming Tsao at Princess Margaret Cancer Centre

Dr. Liu is lead of Princess Margaret CALIBRE program (Cancer And Liquid biopsy, Integrated analysis, Breathomics, Radiomics for Early Detection). In Lung-CALIBRE, the specific focus of this research is to identify biomarkers that can refine the selection for lung cancer CT screening, identify biomarkers that identify patients for specific interventions and develop risk stratification that incorporates biomarkers. He is Principal Investigator of breathomics as a predictive test for immune checkpoint inhibitor efficacy, which is funded through Industry support and the Canadian Cancer Society Research Institute (CCSRI). As co-Principal Applicant, he also co-leads the CIHR funded Lung cancer early detection and classification using methylome analysis of plasma cell free DNA.

Cancers of the Lung Advocacy aNd Scholarship (CLANS) Network

Study Status: active

Institute: Princess Margaret Cancer Centre

Study Purpose: The CLANS Network is a group of researchers and doctors who are working together to understand all the different causes of lung cancer. The more we know about the causes of lung cancer, the more we will be able to stop it from developing in the first place.

Background: Many provinces have started lung cancer screening programs to try and catch cancer earlier. These screening programs are only for people who have smoked a lot of cigarettes and/or cigars in their lifetime. However, more people are getting lung cancer even when they have never smoked. In Canada, one out of every five people who are diagnosed with lung cancer have never smoked.

Study Methods: Lots of studies are already being done in Canada to explore the causes of lung cancer. The CLANS Network will connect these studies to each other. This way, data from one study can be used again in another study, making each study more powerful. The CLANS Network will also help people who aren’t part of any study to join research projects. On the CLANS Network website, anyone can fill out a short survey about who they are, what their health is like, and where in Canada they live. The CLANS Network will use this survey information to match people with lung cancer studies that need them. Altogether, the CLANS Network works to get more people in more studies, all so that we can learn how to stop lung cancer in its tracks

Health Conditions: Cancer, Lungs & Breathing conditions

Dr. Liu graduated sum laude from the University of Toronto medicine program, followed by residencies at the University of Toronto and a fellowship at the Dana Farber Harvard Cancer Center in Boston. He was Assistant Professor of Medicine at Harvard Medical School before returning in 2006 to the Ontario Cancer Institute–Princess Margaret Hospital. Dr. Liu’s major research focus is in molecular prognostic factors and pharmacogenomics of lung and esophageal cancer, with additional interest in head and neck, pancreatic, ovarian and testicular cancers, mesothelioma and thymoma. Trained in clinical and molecular epidemiology, he is the principal investigator of over three dozen completed, ongoing and upcoming cancer pharmacogenomic and molecular epidemiologic analyses of cancer observational studies and clinical trials funded by the National Cancer Institute (US), National Cancer Institute of Canada Clinical Trials Group, Canadian Cancer Society Research Institute, the Canadian Institute of Health Research, the Ontario Institute of Cancer Research, Cancer Care Ontario, Doris Duke Foundation and the Lung Cancer Foundation of America. As Professor of Medicine, Medical Biophysics, Pharmacology and Toxicology, Institute of Medical Science at the University of Toronto, and Professor of Epidemiology at the Dalla Lana School of Public Health at the University of Toronto, and co-author of over 350 peer-reviewed articles, Dr. Liu has research interests in epidemiological outcomes database methods, novel analyses of high dimensionality biologically rich data, pharmacogenomic analyses of conventional and molecularly targeted agents using primary human xenograft models, patient-reported outcomes in pharmacogenomics, and knowledge translation of personalized medicine and pharmacogenomic algorithms into clinical practice. A major area of research is the use of machine learning approaches for analysis of symptoms and toxicity of cancer, and natural language approaches in large scale electronic health data analysis in cancer. He is a member of the Computational Biology and Medicine Program at Princess Margaret Cancer Centre.

For a list of Dr. Liu's publications, please visit PubMed, Scopus or ORCID.

Alan B. Brown Chair in Molecular Genomics
Director, Applied Molecular Profiling Pharmacogenomic Epidemiologic Laboratory, Princess Margaret Cancer Centre
Co-Director, Ontario Patient Reported Outcomes of Symptoms and Toxicity
Co-Director, COMBIEL Training Initiative
Director, CALIBRE
Professor, Departments of Medicine, Medical Biophysics, Pharmacology and Toxicology, and Institute of Medical Science, University of Toronto
Professor of Epidemiology, Dalla Lana School of Public Health, University of Toronto

About UHN Research

Scientists

Resources and Services

Institutional Authorization

Cancers of the Lung Advocacy aNd Scholarship (CLANS) Network